Sciscoper
Sciscoper is an AI powered research assistant that is used to streamline and accelerate the literature review process for STEM researchers, academics, and R&D teams. Researchers often deal with hundreds or thousands of scientific papers scattered across different sources, making it difficult to extract meaningful insights efficiently.
Sciscoper solves this by using AI and natural language processing to automatically:
Summarize scientific papers and research findings.
Extract key insights, concepts, and relationships across documents.
Generate literature reviews with citations in multiple reference styles.
Organize and index papers into a structured, searchable knowledge base for easy discovery.
This allows users to focus less on manual reading and note-taking, and more on analyzing results, identifying research gaps, and producing new scientific knowledge.
Learn more
Resea.AI
Resea AI is a full-featured academic research assistant that autonomously plans, conducts, and writes in-depth academic tasks from literature review to report drafting. It connects seamlessly with major scholarly databases such as Google Scholar, PubMed, and arXiv to source trusted research, then employs its proprietary “Think and Research” engine to determine research direction, core concepts, and writing angles through multi-stage inquiry. Feeding into its AI writing editor, Resea AI is capable of generating documents of unlimited length (even up to 50,000 words), and offers interactive editing for fast refinements. It ensures academic rigor through support for dozens of citation formats with accurate source indexing. It evaluates performance with benchmarks like xBench‑DeepSearch that measure deep research capabilities. Additional use cases include systematic literature reviews, academic outlines, content synthesis, reviewer-perspective feedback, and more.
Learn more
Connected Papers
Connected Papers is a visual tool designed to assist researchers and applied scientists in discovering and exploring academic papers pertinent to their field of work. By inputting a "seed paper," users can generate a graph that displays related papers based on a similarity metric derived from co-citation and bibliographic coupling analyses. This approach allows for the identification of relevant literature, even when direct citations are absent. The resulting graph provides a visual overview of the research landscape, highlighting seminal works and potential areas for further exploration. Connected Papers aims to streamline the literature review process, making it more efficient and comprehensive for researchers.
Learn more
Crescis
Crescis is an AI powered research assistant that creates citation ready literature reviews from either your uploaded PDFs or AI powered searches across millions of scholarly articles. It retrieves relevant open-access papers, summarizes complex research into clear insights, and organizes sources into collections. Generate flawless citations in APA, MLA, Chicago, and more, then compile your findings into ready to edit literature review drafts. By combining search, retrieval, summarization, organization, and citation into one platform, Crescis helps students, researchers, and professionals turn scattered sources into polished academic writing, faster, easier, and more accurately than ever.
Learn more